Traditional brand lift reporting displays multiple metrics – observed lift, statistical significance – that can each tell a different story, making it hard to know how to interpret and act on insights mid-campaign. Additionally, traditional metrics like p-values generally help marketers answer the question: Is a tactic driving non-zero lift in outcomes? In other words, is a tactic driving any lift at all? While these insights are helpful for mid- and post-campaign reporting, they are not particularly conducive to optimization decisions throughout a campaign.

With this in mind, Upwave has introduced a powerful new metric called the Outperformance Indicator, which combines observed lift and confidence levels into a single, sortable metric that answers the optimization question: How much confidence can I have that a tactic is helping the campaign? In other words, what is the probability that this tactic will improve the campaign average? This new metric makes mid-flight campaign optimization decisions easier than ever, providing the clarity, stability, and timeliness that existing brand lift metrics lack.

In the pages below, we’ll detail the methodology behind Upwave’s Outperformance Indicator, sharing multiple use cases to highlight how this metric empowers marketers to make data-driven optimization decisions while a campaign is in flight.